Telemarketing is a well-known form of remote commerce, that is, commerce wherein the person making the sale or taking the sales data is not in the actual physical presence of the potential purchaser or customer. In general operation, a prospective purchaser typically calls a toll-free telephone number, such as an 800 number. The number dialed is associated by the carrier as being associated with the telemarketer, and the dialed number, typically taken automatically from the carrier (long distance) through use of the dialed number identification service (DNIS), is utilized to effect a database access resulting in a “screen pop” of a script on a terminal for the telemarketer. In this way, when a prospective purchaser calls a given telephone number, a telemarketing operator may immediately respond with a script keyed to the goods or services offered. The response may be at various levels of specificity, ranging from a proffer of a single product, e.g., a particular audio recording, or may be for various categories of goods or services, e.g., where the dialed number is responded to on behalf of an entire supplier. Typically, the prospective purchaser is responding to an advertisement or other solicitation, such as a mail order catalog or the like, from which the telephone number is obtained.
In a typical telemarketing application, the item for which the caller makes initial contact is the item which is ordered by the customer. In certain instances, attempts are made to sell other goods or services directly related to the product for which contact was made. For example, if the initial contact was for audio recordings from a given singer, the additional offer may relate to yet further recordings from that same singer. Typically, the correlation between the products offered is predefined, and does not vary depending on the caller.
More generally, the term electronic commerce has been utilized in a broad and evolving manner for remote commerce where at least a portion of the customer-to-seller contact is in electronic form. For example, various forms of electronic on-line shopping services exist. Proprietary content providers in a dial-up content or private networks, such as America Online (AOL), CompuServe and Prodigy, offer various electronic commerce shopping services themselves and access to shopping services by other vendors. Yet other electronic commerce is conducted on publicly available electronic communication networks, such as the Internet which may be accessed through private networks such as AOL or alternatively through access providers such as Earthlink, AT&T WorldNet®, Netcom, or PSI Net. Currently, many Internet based electronic commerce trading sites exist, are interconnected by the Worldwide Web (WWW).
In certain applications, electronic shopping malls are provided, wherein the potential customer is provided access to a menu or other selection of categories of goods and services. Typically, through the use of a menu-driven selection process, the potential customer may locate a desired good or service, or may be presented with information on the goods or services which are available, though not specifically known to the potential customer. By way of example, the menu-based selection system may initially provide the customer with the option for information regarding car purchases, which when selected, presents options regarding makes of cars, which when selected, provides model information regarding cars of a selected model, which in turn then provides information regarding the selected model, and in certain applications, may then lead to price and the ability data, as well as the ability to indicate a desire to purchase the vehicle or to be contacted regarding it. Various search systems or search engines exist which receive a user's input or search terms, which hopefully provide one or more responses or “hits” identifying potential sources of information regarding goods and services.
One form of offer of goods or services in the realm of electronic commerce are the so-called “push” systems. Typically, a user of a system, such as an on-line information provider, e.g., AOL, or a continuous information provider such as PointCast Network, will “push” a product or service at the user of the system, even though the contact with the system was not necessarily for the purpose of any commercial transaction. Typically, the pushed good or service is provided in a non-targeted manner, that is, wherein the proffer is made to many users irrespective of differences between the users.
The use of telephonic systems to effect commercial transactions is now well known. For example, in Katz U.S. Pat. No. 4,792,968, filed Feb. 24, 1987, and issued Dec. 20, 1988, entitled “Statistical Analysis System for Use With Public Communication Facility”, an interactive telephone system for merchandising is disclosed. In one aspect of the disclosure, a caller may interact with an interactive voice response (IVR or ARU) system to effectuate a commercial transaction. For example, the caller may be prompted to identify themselves, such as through entry of a customer number as it may appear on a mail order catalog. In an interactive manner, the caller may be prompted to enter an item number for purchase, utilizing an item number designation from the catalog or otherwise interact with the system to identify the good or service desired. Provision is made for user entry of payment information, such as the entry of a credit card number and type identifier, e.g., VISA, American Express, etc. Options are provided for voice recording of certain information, such as name, address, etc., which is recorded for later processing, or in certain modes of operation, connecting the customer to a live operator for assistance.
In the non-electronic realm, targeted marketing has been utilized in sales efforts. By way of example, targeted marketing such as the mailing or delivery of coupons to potential customers has been made. In certain applications, the selection of customers for receipt of the coupons or other forms of inducement may be based on various factors, such as geographic factors (zip code, zip code plus four, that is the finest zip code based granularity), demographic data, suspected socioeconomic status, or other factors. In yet other applications, targeted marketing is effected through inclusion in specific magazines of selected advertisements or other inducements for perceived segments of subscribers of the periodical.
More recent applications for electronic commerce are described in Katz PCT Publication No. WO94/21084, entitled “Interactive System for Telephone and Video Communication Including Capabilities for Remote Monitoring”, published Sep. 15, 1994. In certain aspects, the application provides systems and methods for conduct of electronic commerce over communication networks, such as through the accessing of such resources via an on-line computer service, wherein the commercial transaction may be effected including some or all of dynamic video, audio and text data. Optionally, the system contemplates the interchange of electronic commerce commercial data, e.g., electronic data interchange (EDI) data, where on-line computer services are used by at least certain of the potential purchasers to interface the system, such as is used to access the Internet.
Various point-of-sale product inducement systems have been proposed. While many of the systems use electronics for their implementation, they do not serve to provide remote commerce. Most typically, the primary application for point-of-sale inducement systems are grocery store, coupon targeting systems. For example, Deaton et al., U.S. Pat. No. 5,592,560 is entitled “Method and System for Building a Database and Performing Marketing Based Upon Prior Shopping History”. The patent discloses a system principally for use in a supermarket. A check verification database is utilized, which includes a scanner to scan the check to obtain identification information. The identification information is used along with historical information regarding the consumer to dispense a sales promotion at the point of sale to the customers who meet predetermined product purchasing history criteria. Various aspects of promotion are provided. For example, a frequent purchaser who is deemed a “good” customer may be rewarded with certain types of coupons. In one aspect, a targeted marketing feature includes “dissemination of point-of-sale coupons and direct mail coupons based upon scanned data”. In this embodiment, information regarding a customer's purchases, such as obtained via the barcode scanner, is reviewed to determine what types of goods the consumer has not purchased, and then attempts to induce them to purchase goods in those different lines. The text provides in pertinent part: “The technique . . . detects whether or not items have been purchased from the meat department, dairy department or deli. Based upon data stored within the computer, the decision is then made as to whether to award a coupon and what type of coupon to award. For example, if the data illustrates that over a period of time a shopper shows a consistent failure to shop at the delicatessen, then when the customer's check identification is scanned into the check reader 119, the processor 110 pulls up the customer's history and generates a coupon to induce the customer to shop at the delicatessen the next time the customer shops. This inducing can be done by providing the customer with a very high valued coupon used only for deli shopping.” (column 67, line 64 to column 68, line 10). This system is attempting to sell on the customers next visit an item outside of the scope of their purchases.
Deaton et al. U.S. Pat. No. 5,638,457 is entitled “Method and System for Building a Database for Use with Selective Incentive Marketing in Response to Customer Shopping Histories”. The system is used for entering a customer's identification code, and includes a memory for storing the previous transaction information and a processor for awarding at a point-of-sale occasion incentive signals representative of “specific customer's dollar volume histories prior to the current visit, said inventive signals having different values in dependence upon different volume histories”. A printer is then used to print out coupons “redeemable at a future time in order to incent said customer to return to the retail store”.
Deaton et al. U.S. Pat. No. 5,201,010 is entitled “Method and System for Building a Database and Performing Marketing Based Upon Prior Shopping History”. The patent discloses the use of a database which is reviewed to determine a list of customers who have not shopped at the store since a preselected date. Those persons are then singled out for marketing in an effort to induce them to return to the store.
Deaton et al. U.S. Pat. No. 5,327,508 is entitled “Method and System for Building a Database and Performing Marketing Based Upon Prior Shopping History”. The patent discloses a system for utilizing a check reader for identification of a customer, barcode reader for detecting UPC's and then circuitry for determining “predetermined infrequent product purchasing history criteria”, which when met, are used to incent the customer to purchase those items deemed infrequently purchased.
Deaton et al. U.S. Pat. No. 5,621,812 is entitled “Method and System for Building a Database for Use With Selective Incentive Marketing in Response to Customer Shopping Histories”. It claims a system including a coupon printer for dispensing sales promotion material, “said sales promotion being efficiently directed towards only the class of said customers who meet predetermined shopping history criteria”.
Deaton et al. U.S. Pat. No. 5,649,114 is entitled “Method and System for Selective Incentive Point-of-Sale Marketing in Response to Customer Shopping Histories”. The patent includes disclosure relating to various forms of identification, such as from a magnetic stripe on a swipe shopping card, a “smart” card or manual input. The system also contemplates in one embodiment “electronic coupons”, such as may be stored on a “smart” card. In yet another aspect, the disclosure relates to providing incentives, and then monitoring and recording the response to the incentive. The incentives are then modified based upon either the success or failure criteria. (FIG. 43). In yet another aspect, the system maintains an “incentive list” for a customer based upon a subset of products that meet a preselected purchasing criteria. (FIG. 46). Targeted marketing may be provided based upon the types of products bought by the purchaser or the department in the store from which the products were bought. (column 98, lines 22-26). In one aspect, the incentive items varies based upon knowledge of the consumer, such as the dollar volume spent per week on items. For example, a $2 off coupon may be a strong incentive for a customer who spends $25 a week, but a less significant incentive for a customer who spends $250 a week.
DeLapa et al. U.S. Pat. No. 5,353,218 is entitled “Focused Coupon System”. The disclosure relates generally to merchandising systems and more particularly to systems for generating and redeeming product discount coupons. The system is said expressly to be “a focused coupon system . . . which is non discriminatory as to consumer income or minority status and which invites participation by any and all consumers, with consumers being removed from the system only upon prolonged non-use”. The purported novelty resides in the inclusion of both identification and coupon information in one bar code, such that the combined information may be read by a single pass over a conventional scanning unit. An initial set of coupons is supplied to a customer. Upon use of at least one of those coupons, a second set may be selected, wherein the second set includes “at least one coupon selected as a function of the coupons the consumer used”. The specification states that: “Other consumption related information pertaining to the consumer may be combined with the history of coupon use in order to select coupons to transmit to the customer. This additional information may be obtained by a telephone interview with the consumer or by the consumer completing a survey of questions.” (column 3, lines 37-43). The selection of coupons or value may be based on various factors, such as providing a relatively larger coupon for a non-customer, or to target a particular department which had not been utilized by the consumer. (See, e.g., column 5, lines 25-37). A consumer profile database is generated, whether by obtaining data from a survey filled out by the consumer or by a telemarketer prompting the consumer to respond to questions. (See, e.g., column 9, lines 6-26).
Humble U.S. Pat. No. 4,825,045 is entitled “System and Method for Check-Out Counter Product Promotion”. A point-of-sale scanner utilizes UPC data to generate a promotion, such as the generation in provision of a coupon to a purchaser.
Schultz et al. U.S. Pat. No. 5,056,019 is entitled “Automated Purchase Reward Accounting System and Method”. The Schultz reference relates to a reward based system which utilizes a scanning system for inputting identification and purchase information. A reward book identifying required purchases is provided. Periodic status reports may be provided to potential customers.
Clarke U.S. Pat. No. 5,502,636 is entitled “Personalized Coupon Generating and Processing System”. The system generates and processes personalized coupons. The system advises the customers of available coupons for predefined products. Customers advise the system of specific desired coupons. Additionally, the system obtains profile information from the responsive consumers. Redemption of coupons is monitored, and the redemption data may be used to validate original consumer responses and to provide future market research opportunities such as polling responsive customers and to enhance specific coupon databases.
Tai U.S. Pat. No. 4,908,761 is entitled “System for Identifying Heavy Product Purchasers Who Regularly Use Manufacturers' Purchase Incentives and Predicting Consumer Promotional Behavior Response Patterns”. Consumers are provided with coupons and “encoding devices”, which are peelable, adhesive backed stickers having a barcode identifying the customer. The coupon preferably includes information regarding the item purchased, such as particular goods, price and size. That information is compiled and used in the next integration of the sending of coupons. An initial list of potential customers of the most likely heaviest purchasers is based on a “geo-demographic lifestyle segmentation”. (column 4, lines 49-51). The demographic segmentation includes characteristics such as income, profession, sex and age. (column 4, lines 54-55). Fifty homogeneous “clusters” or “segments” of types are developed, and then the neighborhoods throughout the United States are associated with a single cluster. Coupons are then distributed and the redemption monitored through the scanning of the encoding device which includes the identification information.
Off et al. U.S. Pat. Nos. 4,910,672, 5,612,868 and 5,173,851 are entitled “Method and Apparatus for Dispensing Discount Coupons” and “Method and Apparatus for Dispensing Discount Coupons in Response to the Purchase of One or More Products”. A discount coupon is provided at a point-of-sale terminal. In one embodiment, the system issues “multiple-trigger” coupons, where the purchase of multiple products of a given type within a category triggers a coupon. Another embodiment prints a “negative” coupon in response to the failure of the customer to purchase a selected trigger item. A third category is a “log-only” operation and a fourth aspect serves to generate an instantly redeemable discount in response to purchases.
The foregoing coupon dispensing systems, by failing to intelligently analyze the available data as to items actually purchased, may generate proposed coupon which are precisely wrong for a customer. For example, rather than attempting to discern that this customer may be a vegetarian based upon the purchases actually made (as indicated, by, e.g., an absence of purchases in the meat department), this system may attempt to sell “hamburgers to Hindus”, a useless, if not offensive, effort.
Various systems have been proposed which seek to measure potential customer interest, or provide simple rules for product selection. For example, Cragun et al. (IBM) U.S. Pat. No. 5,504,675 is entitled “Method and Apparatus for Automatic Selection and Presentation of Sales Promotion Programs”. A sales promotion program is dynamically selected through use of a neural network depending on factors such as the proximity of a person to the display, number of persons responding to the general attract loop and responses to the specific loop programs. The network can be retrained at regular intervals or in response to sales data or changes in the collected data. See, also, Bezus, U.S. Pat. No. 5,715,399, entitled “Secure Method and System for Communicating A List of Credit Card Numbers Over A Non-Secure Networks”.
Hey U.S. Pat. No. 4,996,642 is entitled “System and Method for Recommending Items” and U.S. Pat. No. 4,870,579 is entitled “System and Method of Predicting Subjective Reactions”. The Hey patents disclose a system and method of selectively recommending to a user items such as movies sampled by one or more users in the group but not sampled by the selected user. The recommendation is based in part upon the user's previously sampled items and preferably upon the availability of the item to be recommended. By way of example, a system for recommending a video may be based upon the user's reaction to a movie previously watched, and a positive relationship between that movie and the movie to be recommended, as well as availability of the video.
Various implementations of hardware systems for effecting electronic commerce having been proposed. For example, Chelliah, et al. (Broadvision), U.S. Pat. No. 5,710,887, entitled “Computer System and Method for Electronic Commerce”, incorporated herein by reference, describes one hardware implementation possibly useable for effecting electronic commerce. Numerous other systems to effect functionalities are known to the art.
Mueller et al. U.S. Pat. No. 5,353,219 is entitled “Suggestive Selling in a Customer Self-Ordering System”. A retail store based, touch screen system is used for direct entry by customers of orders. A suggestive selling subroutine displays a screen suggesting items from a primary category in the event that items have not been selected by the customer from a primary category. For example, on a fast food restaurant touch screen order entry system, if the customer has not ordered a drink, but the system otherwise understood that the customer had finished the order entry, would prompt the customer with a display “would you like . . . a refreshing drink?”.
Atcheson et al. U.S. Pat. No. 5,583,763 is entitled “Method and Apparatus for Recommending Selections Based on Preferences in a Multi-User System”. The system determines selections which a user is “likely to be interested in”. This determination is made based upon the user's prior indicated preferences. Various user entered preferences are compared with entries of other users, and users are paired where there are a large number of overlaps in the indicated preferences. The recommended selections are then based upon the as yet nonmatching entries from the paired users.
Johnson U.S. Pat. No. 5,615,342 is entitled “Electronic Proposal Preparation System” and U.S. Pat. No. 5,625,776 is entitled “Electronic Proposal Preparation System for Selling Computer Equipment and Copy Machines”. A display provides product information from which the Applicant selects. Based upon the answers, a customized sales presentation is generated. The system selects information from a variety of sources, such as current pricing information and current product information. A personalized proposal is thereby created.
Suzuki U.S. Pat. No. 5,053,957 is entitled “Electronic Cash Register Having Discount Prices Select by Customer Level”. An electronic cash register receives as input an indication of a “customer level” which is used to select a price for a specified good. The various customer levels may include differentiations based upon whether the customer is an employee, stockholder or the like.
Suda U.S. Pat. No. 5,481,094 is entitled “Point-of-Sale Terminal”. A point-of-sale terminal provides a “package” discount with respect to commodities previously purchased. A scanner monitors items selected and determines whether the package of goods has been purchased. A package may comprise a bundle of goods, such as specified cookies, candies and chocolate or may be in a pair match arrangement, such as a bottle of shampoo and conditioner. Discount prices are then provided if the batch or pair exists within the selected items.
Lockwood U.S. Pat. No. 5,576,951 is entitled “Automated Sales and Services System”. A system composes individualized sales presentations for a prospective customer created from various textual and graphical information data sources to match the customer profile. The sales presentations are composed based upon, among others, customer profile information, and sales agent assessment data.
Walker PCT Publication WO 98/43149 is entitled “Method and System for Processing Supplementary Product Sales at a Point-of-Sale (POS) Terminal”. A POS terminal determines an upsell (as defined therein) to offer in exchange for the change due to a customer in connection with a purchase. Preferably, the POS terminal maintains a database of at least one upsell price in a corresponding upsell to offer a customer in exchange for the change due to the customer. If the customer accepts the upsell, the cashier presses a select button on the terminal. The required payment amount for the customer is then set to the rounded up price. The customer receives the upsell in exchange for the coins due to the customer.
Various financial websites exist which typically permit individual users to access personal account information, typically requiring two items of identification for entry, such as a social security number or customer identification number and password. Typically, in addition to the provision of financial information, such systems permit on-line trading of financial instruments. In one such system, sponsored by Fidelity Investments, denominated WebExpress, a user may provide specific instructions for transactions. If desired, the website may be used, through a hyperlink arrangement, to access further information on financial instruments, such as prospectus information or other historical information. Additionally, the system includes a mutual fund evaluator in which the user is presented with a series of questions relating to specific parameters, such as to the type of fund in which the user is interested, e.g., a growth fund, a growth and income fund . . . , and some measure of their risk averseness. Based upon the user's responses, the system lists various funds deemed to meet those search criteria. However, the system does not provide specific recommendations or optimize the results, but rather, merely lists funds responsive to the criteria selected by the user. Schwab, another financial services provider, also includes an asset allocation module accessible by its website. User entry of information in response to questions (e.g., user's age, years to retirement, risk tolerance, financial goals) is then used to provide a recommended asset allocation, but not specific financial instruments.
Various web-based electronic systems exist wherein some form of item recommendation may be made to the potential purchaser on the user's request. The on-line bookstore AMAZON.COM includes a “Recommendation Center”, which is selected as one option by the user. An “instant recommendations” feature makes recommendations based on the user's past purchases at AMAZON.COM. The BookMatcher permits user entry of authors and book type (e.g., histories, mysteries) and to indicate whether they like them or dislike them, and the MoodMatcher permits user entry of occasions, whereupon recommendations are made. The Customer Buzz feature identifies titles other customers have reviewed in the greatest number and with the greatest passion. Finally, the “if you like this author . . . ” feature permits user entry of author identity, and the system suggests another believed to be of interest to the user. While not conceded to be prior art, Amazon.com, Inc. has been issued U.S. Pat. No. 6,064,980, entitled “System and Methods for Collaborative Recommendations”.
Various data mining or collaborative filtering systems exist. For example, U.S. Pat. No. 5,970,482 entitled “System for Data Mining Using Neuroagents” discloses a system in which an automated and unified data mining system is provided for the stated purpose of providing an explicitly predictive knowledge model. Another patent stated to disclose an electronic information system for determining predictive utility of prediction techniques in ascertaining which items are valued is U.S. Pat. No. 5,842,199, entitled “System, Method and Article of Manufacture for Using Receiver Operating Curve to Evaluate Predictive Utility”.
Yet another deficiency of certain of the prior art systems is in their failure to incentivise the potential customer in real time. Often times, the best time to offer incentives or alternatives for purchases when the customer has already manifested a desire or interest to purchase. Despite the efforts made over a significant period, an effective, useful system for the intelligent, automated provision of goods and services in the telephonic and electronic commerce areas has been made.